NCT06604689

AI-guided Prognostication and Cranial Radiotherapy Optimization in EGFR-TKI-treated Non-small Cell Lung Cancer Patients With Baseline Brain Metastases

Artificial Intelligence-guided Prognostication and Cranial Radiotherapy Optimization in First-line Third-generation EGFR-TKI-treated EGFR-mutant Non-small Cell Lung Cancer With Baseline Brain Metastases: a Multicenter, Observational Study

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 800 (estimated)
• Sponsor: Fudan University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The goal of this observational study is to extract the imaging features of brain lesions and primary lung lesions in NSCLC patients with brain metastases by deep learning, as well as common clinicopathological parameters, which are used to construct a multimode model that can accurately predict the treatment efficacy and survival of the third-generation EGFR-TKI treatment, and to use the model to assist in screening high-risk populations suitable for upfront cranial radiotherapy. Participants receiving third-generation EGFR-TKI treatment will be enrolled in our study and we will collect their regular contrast-enhanced chest CT and contrast-enhanced brain MRI for model construction.

Conditions

• NSCLC (Advanced Non-small Cell Lung Cancer)
• Brain Metastasases

Interventions

Type	Name	Description
DRUG	third-generation EGFR TKIs (Almonertinib/Furmonertinib/Osimertinib)	EGFR-mutated NSCLC patients with brain metastases who met the inclusion and exclusion criteria, would receive first-line third-generation EGFR-TKI treatment (monotherapy or combined with upfront cranial radiotherapy)

Timeline

• Start date: 2024-09-30
• Primary completion: 2025-04-01
• Completion: 2025-10-01
• First posted: 2024-09-19
• Last updated: 2024-11-12

Locations

1 site across 1 country: China